Yubing Lu
- Neurology top 1%
- Molecular Biology top 10%
- Genetics top 1%
- Cellular and Molecular Neuroscience top 5%
- Physiology top 10%
- Co-authors
- Fen‐Biao GaoSandra AlmeidaLeonard PetrucelliBruce L. MillerDejun YangTania F. GendronHélène TranNisha M. Badders
- Topics
- Amyotrophic Lateral Sclerosis Research (10 papers)Neurogenetic and Muscular Disorders Research (6 papers)Metalloenzymes and iron-sulfur proteins (6 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Yubing Lu
28 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Neurology 1.1k
- Molecular Biology 1.0k
- Genetics 687
- Cellular and Molecular Neuroscience 367
- Physiology 255
Countries citing papers authored by Yubing Lu
This map shows the geographic impact of Yubing Lu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yubing Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yubing Lu more than expected).
Fields of papers citing papers by Yubing Lu
This network shows the impact of papers produced by Yubing Lu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yubing Lu. The network helps show where Yubing Lu may publish in the future.
Co-authorship network of co-authors of Yubing Lu
This figure shows the co-authorship network connecting the top 25 collaborators of Yubing Lu. A scholar is included among the top collaborators of Yubing Lu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yubing Lu. Yubing Lu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 11 | |
| 3 | 24 | |
| 4 | 11 | |
| 5 | Poly(GR) in C9ORF72 -Related ALS/FTD Compromises Mitochondrial Function and Increases Oxidative Stress and DNA Damage in iPSC-Derived Motor Neuronsbreakdown → | 315 |
| 6 | 144 | |
| 7 | 96 | |
| 8 | GGGGCC repeat expansion in C9orf72 compromises nucleocytoplasmic transportbreakdown → | 600 |
| 9 | 58 | |
| 10 | 111 | |
| 11 | 48 | |
| 12 | 17 | |
| 13 | 31 | |
| 14 | 105 | |
| 15 | 65 | |
| 16 | Purification and Activation In Vitro of MoFe Protein from a nifE Deleted Mutant Strain of Azotobacter vinelandii | 2 |
| 17 | Crystal Growth of Nitrogenase CrFe Protein and MnFe Protein in Space | 1 |
| 18 | Purification and Characterization of Cr-containing Nitrogenase Component I | 2 |
| 19 | Crystalline Growth of Nitrogenase CrFe Protein | 1 |
| 20 | Growth of the crystals of nitrogenase MnFe protein | 1 |
About Yubing Lu
Yubing Lu is a scholar working on Neurology, Aging and Genetics, having authored 29 papers that have together received 1.8k indexed citations. Recurring topics across this work include Amyotrophic Lateral Sclerosis Research (10 papers), Neurogenetic and Muscular Disorders Research (6 papers) and Metalloenzymes and iron-sulfur proteins (6 papers). The work is most often cited by research in Neurology (1.1k citations), Genetics (687 citations) and Aging (37 citations). Yubing Lu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Fen‐Biao Gao, Sandra Almeida, Leonard Petrucelli, Bruce L. Miller, Dejun Yang, Tania F. Gendron, Hélène Tran, Nisha M. Badders, Hong Joo Kim and Kyung‐Ha Lee. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.